Africa’s climate future hangs in a delicate balance. With each passing year, extreme weather events become more frequent and destructive. Nigeria, in particular, faces climate threats such as recurring floods in Lagos and Bayelsa, increasing desertification in the north, and coastal erosion in the south. Yet, while these challenges are severe, they are not insurmountable.

In line with the essence of this reflection, I have offered similar interventions through my recent Nigerian Tribune interview titled ‘Climate change: Govt, citizens’ partnership vital to good public health, environmental outcomes’ and my The Guardian article titled ‘Flooding: climate expert urges FG to increase effort towards environmental solutions’. These articles show how Nigeria can leverage artificial intelligence (AI) and machine learning (ML) technologies to address climate challenges.

Around the world, AI is deployed to understand, predict, and respond to climate risks in ways that traditional methods cannot. If Nigeria is to build lasting climate resilience, it must draw from international examples while fostering its AI-driven environmental intelligence systems. Across the United Kingdom and the United States, governments and private sectors have embraced AI as a core component of climate management.

In the UK, institutions like the Met Office and the Environment Agency are utilising AI-powered models for real-time flood forecasting, long-term climate projections, and infrastructure planning. DeepMind, a UK-based AI lab, collaborated with Google to significantly reduce energy consumption in data centres through reinforcement learning, cutting cooling needs by up to 40 per cent. The Centre for Greening Finance and Investment (CGFI) has adopted AI to assess climate risks across financial systems, using machine learning to map vulnerabilities in national infrastructure.

The US offers another model, notable for the scale and depth of its AI-climate integration. NASA’s Earth Exchange (NEX) platform combines satellite data and machine learning to monitor deforestation, drought patterns, and carbon fluxes. The National Oceanic and Atmospheric Administration (NOAA) uses deep learning to interpret oceanic and atmospheric datasets, supporting early warnings for hurricanes and wildfires. At the Department of Energy, the Artificial Intelligence for Earth System Predictability (AI4ESP) initiative is revolutionising climate science by integrating AI into Earth system models, allowing scientists to simulate future scenarios with greater precision. Meanwhile, companies like ClimateAI are using AI to predict drought risk and guide farmers’ planting strategies, while Cervest offers asset-level climate intelligence to corporations managing physical infrastructure.

In Nigeria, however, the picture remains different. Despite recurring climate emergencies, such as the 2022 floods that displaced more than 1.4 million people, the national approach still leans heavily on reactive emergency response. Forecasts arrive late, data are fragmented across agencies, and communities most affected often lack the tools or information to prepare.

In The Guardian article titled ‘Geologist reveals how govt can build adaptive strategies for climate management’, Becky Peremoboere Bamiekumo addressed some of these challenges. Also, Ugochukwu Charles Akajiaku, in The Guardian article titled ‘Nigerian govt, corporations should leverage AI for climate management ─ Akajiaku’, shared his expertise on how these climate problems could be managed. Furthermore, in a Nigerian Tribune interview titled ‘Climate-safe future possible when governments, citizens work together to actualise green policies’, Prince Chukwuemeka spoke extensively on these issues. These cited articles reveal the gaps that AI and machine learning can fill in addressing climate challenges in Nigeria.

It is within these gaps that AI can offer transformative value. AI-powered flood forecasting systems, when linked with satellite data, rainfall sensors, and hydrological models, can simulate flooding in real-time and issue early alerts. These tools can enable state governments to pre-position relief materials, guide evacuations, and protect vulnerable populations before the damage is done. In agriculture, which employs a majority of Nigeria’s workforce, AI can forecast seasonal yields, detect crop diseases early through remote sensing, and recommend climate-smart practices. By training machine learning models on historical weather and soil data, the government could deliver localised, actionable advice to farmers through mobile platforms, which would help build food security in the face of unpredictable climate conditions.

Of course, adopting AI at this scale requires more than interest — it demands investment, coordination, and vision. Nigeria faces three primary challenges in this regard. First is the issue of data access. While agencies like NiMet, NASRDA, and NIHSA collect valuable environmental and climate data, much of it remains siloed or outdated. Establishing an open-access national climate data platform, as done in the UK and US, would provide AI developers, researchers, and policymakers with the raw materials needed to build effective climate tools. Second, there is the issue of talent. While the country’s data science ecosystem is growing — with hubs like Data Science Nigeria and AI Saturdays — much of the expertise remains concentrated in urban centres. Expanding AI training to include climate-specific applications in rural and climate-vulnerable areas would empower a broader generation of innovators. Lastly, Nigeria needs a clear policy framework that integrates AI into climate adaptation plans. A national strategy focused on ‘AI for Climate Resilience’ would help align resources, set research priorities, and foster public-private partnerships. Notably, the call for such a shift is already gaining traction.

Elsewhere in Africa, countries like Kenya and Ghana are already moving ahead. Kenyan startup Selina Wamucii uses AI to predict weather impacts on smallholder farmers, while in Ghana, drone and AI technologies are helping map erosion and deforestation in real-time.

Nigeria, with its population size, tech talent, and environmental diversity, is well-positioned to lead the continent in climate-tech innovation, but it must act deliberately. By supporting startups focused on climate AI, investing in public data systems, and aligning national goals with AI capabilities, Nigeria can make this leap. The consequences of inaction are severe. Delays in forecasting floods, food insecurity due to climate variability, unmanaged urban heatwaves, and unchecked environmental degradation will cost not only money but lives. However, by learning from the UK and the US, and by listening to local experts, Nigeria can forge a different path, one where climate shocks are anticipated, not just endured.

AI is not a silver bullet, but it is a powerful tool in the fight for a climate-resilient Nigeria. With political will, institutional cooperation, and targeted investment, it can be the force that transforms Nigeria’s climate crisis into an opportunity for leadership, innovation, and survival.

Imoni, a climate tech and public health expert, writes from Port Harcourt